Human EEG Activity Research Articles

Exploration of basil (Ocimum basilicum) essential oil profiles using E-nose and GC–MS combined with GC-O and inhalation effects on the human EEG topography and tomography (s-LORETA) and blood pressure

This study aimed to investigate the changes in human EEG activity, Brodmann area, and blood pressure during basil essential oil inhalation. Seven odor-active compounds were detected by GC–MS combined with GC–olfactometry, and three abundant volatile compounds were detected by electronic nose. Linalool was simultaneously regarded as a major volatile compound. The systolic and diastolic blood pressures and pulse levels showed a decreasing trend during BEO inhalation. The relative beta and gamma waves in most brain regions changed during BEO inhalation. The gamma waves decreased, whereas the beta waves increased during BEO inhalation. In particular, the beta waves in the left frontal and right parietal regions and Brodmann area 38 significantly increased during inhalation using sLORETA. Accordingly, these results were highly associated with reduced stress responses by decreased gamma waves, blood pressures, and pulse levels and improved language-related functions by the increased beta wave at Brodmann area 38.

Brain rhythms: How control gets into working memory

New research suggests that frontal midline theta EEG activity in humans controls activity in parietal cortex associated with memory maintenance. In turn, the speed of this frontal theta is modulated by the number of items to be handled, potentially indicating strong bidirectional communication within a fronto-parietal network.

Psilocin, LSD, mescaline, and DOB all induce broadband desynchronization of EEG and disconnection in rats with robust translational validity

Serotonergic psychedelics are recently gaining a lot of attention as a potential treatment of several neuropsychiatric disorders. Broadband desynchronization of EEG activity and disconnection in humans have been repeatedly shown; however, translational data from animals are completely lacking. Therefore, the main aim of our study was to assess the effects of tryptamine and phenethylamine psychedelics (psilocin 4 mg/kg, LSD 0.2 mg/kg, mescaline 100 mg/kg, and DOB 5 mg/kg) on EEG in freely moving rats. A system consisting of 14 cortical EEG electrodes, co-registration of behavioral activity of animals with subsequent analysis only in segments corresponding to behavioral inactivity (resting-state-like EEG) was used in order to reach a high level of translational validity. Analyses of the mean power, topographic brain-mapping, and functional connectivity revealed that all of the psychedelics irrespective of the structural family induced overall and time-dependent global decrease/desynchronization of EEG activity and disconnection within 1–40 Hz. Major changes in activity were localized on the large areas of the frontal and sensorimotor cortex showing some subtle spatial patterns characterizing each substance. A rebound of occipital theta (4–8 Hz) activity was detected at later stages after treatment with mescaline and LSD. Connectivity analyses showed an overall decrease in global connectivity for both the components of cross-spectral and phase-lagged coherence. Since our results show almost identical effects to those known from human EEG/MEG studies, we conclude that our method has robust translational validity.

Photobiological Neuromodulation of Resting-State EEG and Steady-State Visual-Evoked Potentials by 40 Hz Violet Light Optical Stimulation in Healthy Individuals

Photobiological neuromodulation and its clinical application has been investigated in recent years. The response of the gamma-oscillation to human visual stimuli is known to be both burst and resonant in nature, and the coupling between alpha and gamma oscillations may play a functional role in visual processing. To date, there is no study that examined the effects of gamma-frequency violet light (VL) stimulation on human electroencephalography (EEG). In this study, we investigated the neurophysiological changes induced by light stimulation using EEG. The purpose of this study was to evaluate the specific effects of 40 Hz gamma-frequency VL stimulation on EEG activity by comparing the effects of white light (WL) with the same condition. Twenty healthy participants (10 females: 37.5 ± 14.3 years; 10 males: 38.0 ± 13.3 years) participated in this study and the following results were observed. First, when compared with the power spectrum density (PSD) of baseline EEG, 40 Hz-WL induced significant increase of PSD in theta band. Second, compared the PSDs between EEG with 40 Hz-VL and EEG with 40 Hz-WL, 40 Hz-VL induced significantly lower enhancement in delta and theta bands than 40 Hz-WL. Third, when focused on the occipital area, negative peak of VEP with 40 Hz-VL was smaller than that of 40 Hz-WL. Fourth, 40 Hz-VL induced an increase of alpha-gamma coupling during the VEP at the F5 electrode site as well as post-EEG at the C4 electrode site, compared with baseline EEG. Thus, the present study suggested that 40 Hz-VL stimulation may induce unique photobiological neuromodulations on human EEG activity.

Perturbing Neural Representations of Working Memory with Task-irrelevant Interruption

Working memory maintains information so that it can be used in complex cognitive tasks. A key challenge for this system is to maintain relevant information in the face of task-irrelevant perturbations. Across two experiments, we investigated the impact of task-irrelevant interruptions on neural representations of working memory. We recorded EEG activity in humans while they performed a working memory task. On a subset of trials, we interrupted participants with salient but task-irrelevant objects. To track the impact of these task-irrelevant interruptions on neural representations of working memory, we measured two well-characterized, temporally sensitive EEG markers that reflect active, prioritized working memory representations: the contralateral delay activity and lateralized alpha power (8-12 Hz). After interruption, we found that contralateral delay activity amplitude momentarily sustained but was gone by the end of the trial. Lateralized alpha power was immediately influenced by the interrupters but recovered by the end of the trial. This suggests that dissociable neural processes contribute to the maintenance of working memory information and that brief irrelevant onsets disrupt two distinct online aspects of working memory. In addition, we found that task expectancy modulated the timing and magnitude of how these two neural signals responded to task-irrelevant interruptions, suggesting that the brain's response to task-irrelevant interruption is shaped by task context.

Alpha-band Activity Tracks the Zoom Lens of Attention.

Voluntary control over spatial attention has been likened to the operation of a zoom lens, such that processing quality declines as the size of the attended region increases, with a gradient of performance that peaks at the center of the selected area. Although concurrent changes in activity in visual regions suggest that zoom lens adjustments influence perceptual stages of processing, extant work has not distinguished between changes in the spatial selectivity of attention-driven neural activity and baseline shift of activity that can increase mean levels of activity without changes in selectivity. Here, we distinguished between these alternatives by measuring EEG activity in humans to track preparatory changes in alpha activity that indexed the precise topography of attention across the possible target positions. We observed increased spatial selectivity in alpha activity when observers voluntarily directed attention toward a narrower region of space, a pattern that was mirrored in target discrimination accuracy. Thus, alpha activity tracks both the centroid and spatial extent of covert spatial attention before the onset of the target display, lending support to the hypothesis that narrowing the zoom lens of attention shapes the initial encoding of sensory information.

EEG-based assessment in novice and experienced drivers' braking behaviour during simulated driving

The driver is an essential factor in the traffic system, and inexperienced drivers are special high-risk groups. We used electroencephalography (EEG) and reaction time to quantify the differences between experienced and novice drivers' risk perception and braking behaviour in a driving simulator. Twenty-seven participants were asked to drive through a 12-km dynamic scenario with EEG signals recorded simultaneously. There are mainly four frequency bands for human EEG activity: alpha, beta, theta, and delta. The power spectral density (PSD) of beta activity was analysed because it dominated when drivers braked in an emergency. The results indicate that the indicators of β activity and reaction time discriminated between the novice and experienced drivers. The reaction time of drivers was related to the increment of the β activity, indicating that the driver's risk perception stage will affect their risk reaction. The study provides us with the operating performance and internal physiological activities of drivers in the braking process.

EEG-based assessment in novice and experienced drivers' braking behaviour during simulated driving

The driver is an essential factor in the traffic system, and inexperienced drivers are special high-risk groups. We used electroencephalography (EEG) and reaction time to quantify the differences between experienced and novice drivers' risk perception and braking behaviour in a driving simulator. Twenty-seven participants were asked to drive through a 12-km dynamic scenario with EEG signals recorded simultaneously. There are mainly four frequency bands for human EEG activity: alpha, beta, theta, and delta. The power spectral density (PSD) of beta activity was analysed because it dominated when drivers braked in an emergency. The results indicate that the indicators of β activity and reaction time discriminated between the novice and experienced drivers. The reaction time of drivers was related to the increment of the β activity, indicating that the driver's risk perception stage will affect their risk reaction. The study provides us with the operating performance and internal physiological activities of drivers in the braking process.

Spectral analysis versus signal complexity methods for assessing attention related activity in human EEG.

We aimed to find the most effective analytical method for assessment of attention related activity to be used in neurofeedback training. We compared commonly used spectral EEG methods with those measuring signal complexity - based on calculation of entropy and fractal dimension. The 14 subjects were examined with a modified delayed matching-to-sample task. All investigated methods revealed significant differences of EEG signals recorded in control and attentional trials, however the selection of signals with such differences varied between subjects and applied methods. The results indicated: (i) the importance of the individual analysis of signals from each subject and session, (ii) benefits of applying signal complexity methods to support spectral analysis in a further application and (iii) an advantage of the signal complexity method, carrying information of assembles of spectral components, over common spectral methods.

A time series analysis to investigate the effect of inhalation of aldehyde C10 on the human EEG activity

IntroductionDecanal (C10) is an important aldehyde, extensively used to enhance floral and citrus notes in various perfumery products. It is well-known that the human electroencephalographic (EEG) activity is highly susceptible to change due to the exposure of fragrances. However, the EEG findings exhibit non-stationary behavior in terms of analysis and recording time. Hence, the present study aimed to investigate the effect of inhalation of aldehyde C10 on the human EEG activity with respect to time series analysis. MethodsTwenty healthy volunteers (10 men and 10 women) participated in the EEG study. The EEG data were recorded from 8 channels according to the International 10–20 System. The EEG readings were analyzed for every second by splitting the total 30 s data during the no odor and C10 odor exposures. ResultsThe exposure of C10 odor produced significant changes (p < 0.05) in all the absolute waves at a certain time during the time series analysis. The results revealed that all absolute waves significantly decreased during the first 13 s period of time due to the exposure of C10 odor. After that, absolute alpha, absolute slow alpha, and absolute fast alpha markedly increased. Furthermore, the exposure to C10 appears to mainly affect the frontal regions, especially the left frontal region (F3) compared with other regions. ConclusionOur data suggest that the EEG activity of C10 odor is highly unstable in the time series analysis, thereby analysis time could play a key role in the EEG response to olfactory stimulation.

Multivariate classification of neuroimaging data with nested subclasses: Biased accuracy and implications for hypothesis testing.

Biological data sets are typically characterized by high dimensionality and low effect sizes. A powerful method for detecting systematic differences between experimental conditions in such multivariate data sets is multivariate pattern analysis (MVPA), particularly pattern classification. However, in virtually all applications, data from the classes that correspond to the conditions of interest are not homogeneous but contain subclasses. Such subclasses can for example arise from individual subjects that contribute multiple data points, or from correlations of items within classes. We show here that in multivariate data that have subclasses nested within its class structure, these subclasses introduce systematic information that improves classifiability beyond what is expected by the size of the class difference. We analytically prove that this subclass bias systematically inflates correct classification rates (CCRs) of linear classifiers depending on the number of subclasses as well as on the portion of variance induced by the subclasses. In simulations, we demonstrate that subclass bias is highest when between-class effect size is low and subclass variance high. This bias can be reduced by increasing the total number of subclasses. However, we can account for the subclass bias by using permutation tests that explicitly consider the subclass structure of the data. We illustrate our result in several experiments that recorded human EEG activity, demonstrating that parametric statistical tests as well as typical trial-wise permutation fail to determine significance of classification outcomes correctly.

Retrospective Cues Mitigate Information Loss in Human Cortex during Working Memory Storage.

Working memory (WM) enables the flexible representation of information over short intervals. It is well established that WM performance can be enhanced by a retrospective cue presented during storage, yet the neural mechanisms responsible for this benefit are unclear. Here, we tested several explanations for retrospective cue benefits by quantifying changes in spatial WM representations reconstructed from alpha-band (8-12 Hz) EEG activity recorded from human participants (both sexes) before and after the presentation of a retrospective cue. This allowed us to track cue-related changes in WM representations with high temporal resolution (tens of milliseconds). Participants encoded the locations of two colored discs for subsequent report. During neutral trials, an uninformative cue instructed participants to remember the locations of both discs across a blank delay, and we observed a monotonic decrease in the fidelity of reconstructed spatial WM representations with time. During valid trials, a 100% reliable cue indicated that the color of the disc participants would be probed to report. Critically, valid cues were presented immediately after the termination of the encoding display ["valid early" (VE) trials] or midway through the delay period ["valid late" (VL) trials]. During VE trials, the gradual loss of location-specific information observed during neutral trials was eliminated, while during VL trials it was partially reversed. Our findings suggest that retrospective cues engage several different mechanisms that together serve to mitigate information loss during WM storage.SIGNIFICANCE STATEMENT Working memory (WM) performance can be improved by a cue presented during storage. This effect, termed a retrospective cue benefit, has been used to explore the limitations of attentional prioritization in WM. However, the mechanisms responsible for retrospective cue benefits are unclear. Here we tested several explanations for retrospective cue benefits by examining how they influence WM representations reconstructed from human EEG activity. This approach allowed us to visualize, quantify, and track the effects of retrospective cues with high temporal resolution (on the order of tens of milliseconds). We show that under different circumstances retrospective cues can both eliminate and even partially reverse information loss during WM storage, suggesting that retrospective cue benefits have manifold origins.

Neural bases of rhythmic entrainment in humans: critical transformation between cortical and lower-level representations of auditory rhythm.

The spontaneous ability to entrain to meter periodicities is central to music perception and production across cultures. There is increasing evidence that this ability involves selective neural responses to meter-related frequencies. This phenomenon has been observed in the human auditory cortex, yet it could be the product of evolutionarily older lower-level properties of brainstem auditory neurons, as suggested by recent recordings from rodent midbrain. We addressed this question by taking advantage of a new method to simultaneously record human EEG activity originating from cortical and lower-level sources, in the form of slow (<20Hz) and fast (>150Hz) responses to auditory rhythms. Cortical responses showed increased amplitudes at meter-related frequencies compared to meter-unrelated frequencies, regardless of the prominence of the meter-related frequencies in the modulation spectrum of the rhythmic inputs. In contrast, frequency-following responses showed increased amplitudes at meter-related frequencies only in rhythms with prominent meter-related frequencies in the input but not for a more complex rhythm requiring more endogenous generation of the meter. This interaction with rhythm complexity suggests that the selective enhancement of meter-related frequencies does not fully rely on subcortical auditory properties, but is critically shaped at the cortical level, possibly through functional connections between the auditory cortex and other, movement-related, brain structures. This process of temporal selection would thus enable endogenous and motor entrainment to emerge with substantial flexibility and invariance with respect to the rhythmic input in humans in contrast with non-human animals.

Multichannel sleep spindle detection using sparse low-rank optimization

BackgroundAutomated single-channel spindle detectors, for human sleep EEG, are blind to the presence of spindles in other recorded channels unlike visual annotation by a human expert. New methodWe propose a multichannel spindle detection method that aims to detect global and local spindle activity in human sleep EEG. Using a non-linear signal model, which assumes the input EEG to be the sum of a transient and an oscillatory component, we propose a multichannel transient separation algorithm. Consecutive overlapping blocks of the multichannel oscillatory component are assumed to be low-rank whereas the transient component is assumed to be piecewise constant with a zero baseline. The estimated oscillatory component is used in conjunction with a bandpass filter and the Teager operator for detecting sleep spindles. Results and comparison with other methodsThe proposed method is applied to two publicly available databases and compared with 7 existing single-channel automated detectors. F1 scores for the proposed spindle detection method averaged 0.66 (0.02) and 0.62 (0.06) for the two databases, respectively. For an overnight 6 channel EEG signal, the proposed algorithm takes about 4min to detect sleep spindles simultaneously across all channels with a single setting of corresponding algorithmic parameters. ConclusionsThe proposed method attempts to mimic and utilize, for better spindle detection, a particular human expert behavior where the decision to mark a spindle event may be subconsciously influenced by the presence of a spindle in EEG channels other than the central channel visible on a digital screen.

EEG Activities and the Sustained Attention Performance

We investigated the relations between EEG activity and sustained attention in humans. A visual version of the conjunctive continuous performance task (CCPT-V) was used as a measure of sustained attention. Twenty university students voluntarily participated in the study; they were divided into two groups, good and weak, according to their results in the CCPT-V. The spectral power of EEG recorded from Fz, Cz, and Pz was analyzed under three conditions (eyes open, eyes closed, and CCPT-V) in four frequency ranges, theta (4–8 Hz), alpha (8–13 Hz), beta (13–30 Hz) and gamma (30–60 Hz) in three channels. Results of repeatedmeasures MANOVA showed the significance of the effects of conditions and channels with respect to the alpha and theta but not to the beta and gamma powers. There was no significant effect of the group, but, when comparing the alpha power under three conditions, the good group showed lower spectral powers. It has been concluded that cerebral neuronal systems producing alpha and theta oscillations play a role in sustained attention, and this can be shown by EEG recording and in the respective test.

Effect of essential oil and supercritical carbon dioxide extract from the root of Angelica gigas on human EEG activity

ObjectivesThe present study aimed to investigate the effect of inhalation of essential oil (EO) and supercritical carbon dioxide extract (SC-CO2) from the root of A. gigas on human electroencephalographic (EEG) activity. Materials and methodsFor this purpose, the EO was obtained from the root of A. gigas by steam distillation and SC-CO2 was obtained at 50 °C and 400 bar for 1 h. The EEG readings were recorded using the QEEG-8 system from 8 electrode sites according to the International 10-20 system. ResultsIn the EEG study, the absolute low beta (left temporal and left parietal) activity significantly increased during the inhalation of EO. In the case of SC-CO2 inhalation, there was no significant change in absolute waves. ConclusionThe results revealed that the EO of A. gigas root produced significant changes in the absolute low beta activity and these changes may enhance the language learning abilities of human brain.

Low-frequency theta oscillations in the human hippocampus during real-world and virtual navigation

Low-Frequency Oscillations (LFO) in the range of 7–9 Hz, or theta rhythm, has been recorded in rodents ambulating in the real world. However, intra-hippocampus EEG recordings during virtual navigation in humans have consistently reported LFO that appear to predominate around 3–4 Hz. Here we report clear evidence of 7–9 Hz rhythmicity in raw intra-hippocampus EEG traces during real as well as virtual movement. Oscillations typically occur at a lower frequency in virtual than real world navigation. This study highlights the possibility that human and rodent hippocampal EEG activity are not as different as previously reported and this difference may arise, in part, due to the lack of actual movement in previous human navigation studies, which were virtual.

Upper Beta Band Oscillations in Human Premotor Cortex Encode Subjective Choices in a Vibrotactile Comparison Task.

Comparisons of sequentially presented vibrotactile frequencies have been extensively studied using electrophysiological recordings in nonhuman primates. Although neural signatures for working memory aspects of such tasks were recently also identified in human oscillatory EEG activity, homologue correlates of the comparison process are yet unknown. Here, we recorded EEG activity while participants decided which of two sequentially presented vibrotactile stimuli had a higher frequency. Because choices in this type of task are known to be systematically biased by the time-order effect, we applied Bayesian modeling to account for individual choice behavior. Using model-based EEG analysis, we found that upper beta band amplitude (∼20-30 Hz) was modulated by participants' choices. The modulation emerged ∼750 msec before a behavioral response was given and was source-localized to premotor areas.Importantly, the choice-dependent modulation of beta band amplitude was invariant to different motor response mappings and reflected the categorical outcome of the subjective comparison between the two frequencies. Consistently, this pattern was evident for both correct and incorrect trials, indicating that the beta band amplitude mirrors the internal representation of the comparison outcome. Our data complement previous findings in nonhuman primates and corroborate that the beta band activity in premotor areas reflects the categorical outcome of a sensory comparison prior to translation into an effector-specific motor command.

The role of blood vessels in high-resolution volume conductor head modeling of EEG

Reconstruction of the electrical sources of human EEG activity at high spatio-temporal accuracy is an important aim in neuroscience and neurological diagnostics. Over the last decades, numerous studies have demonstrated that realistic modeling of head anatomy improves the accuracy of source reconstruction of EEG signals. For example, including a cerebro-spinal fluid compartment and the anisotropy of white matter electrical conductivity were both shown to significantly reduce modeling errors. Here, we for the first time quantify the role of detailed reconstructions of the cerebral blood vessels in volume conductor head modeling for EEG. To study the role of the highly arborized cerebral blood vessels, we created a submillimeter head model based on ultra-high-field-strength (7T) structural MRI datasets. Blood vessels (arteries and emissary/intraosseous veins) were segmented using Frangi multi-scale vesselness filtering. The final head model consisted of a geometry-adapted cubic mesh with over 17×106 nodes. We solved the forward model using a finite-element-method (FEM) transfer matrix approach, which allowed reducing computation times substantially and quantified the importance of the blood vessel compartment by computing forward and inverse errors resulting from ignoring the blood vessels. Our results show that ignoring emissary veins piercing the skull leads to focal localization errors of approx. 5 to 15mm. Large errors (>2cm) were observed due to the carotid arteries and the dense arterial vasculature in areas such as in the insula or in the medial temporal lobe. Thus, in such predisposed areas, errors caused by neglecting blood vessels can reach similar magnitudes as those previously reported for neglecting white matter anisotropy, the CSF or the dura — structures which are generally considered important components of realistic EEG head models. Our findings thus imply that including a realistic blood vessel compartment in EEG head models will be helpful to improve the accuracy of EEG source analyses particularly when high accuracies in brain areas with dense vasculature are required.

Transitory effect of spike and spike-and-wave discharges on EEG power in children

Background: Spikes and spike-and-wave discharges on the EEG of children are a strong biomarker of epilepsy. There is increasing evidence that these EEG abnormalities also impair brain function and result in transitory cognitive impairment. Studies in animal models have shown that EEG spikes alters single cell firing and that such impairment in firing may extend beyond the duration of the spike-and-wave discharge. Whether interictal epileptiform discharges have lasting effects on EEG activity in humans is not known. Methods and Results: The EEGs of 60 consecutive children with focal or interictal spike-and-wave discharges were evaluated using power spectral analysis to determine if there were any changes in power spectra from before to after the interictal abnormalities. Neither focal spike-and-wave nor generalized spike-and-wave discharges had any effect on the EEG frequency or spectral power following the discharge. Conclusion: While interictal EEG discharges temporarily alter neural activity during the duration of the spike-and-wave discharge, there is no evidence that alterations of spectral power continue beyond the duration of the interictal discharge. The effects of interictal activity on EEG rhythms therefore appear to be quite transient and confined to the duration of the interictal discharge.